{"id":"W4392158189","doi":"10.1109/globecom54140.2023.10436917","title":"Using Early Exits for Fast Inference in Automatic Modulation Classification","year":2023,"lang":"en","type":"article","venue":"","topic":"Wireless Signal Modulation Classification","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Inference; Modulation (music); Artificial intelligence; Speech recognition; Pattern recognition (psychology)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002642013,0.001338498,0.001007433,0.0009118624,0.0007078889,0.001406108,0.001897651,0.001366223,0.004127918],"category_scores_gemma":[0.01022997,0.0006517267,0.0006444993,0.0005584685,0.001046211,0.002829565,0.001971719,0.004039925,0.00135631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009166783,"about_ca_system_score_gemma":0.001346293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003044911,"about_ca_topic_score_gemma":0.005631013,"domain_scores_codex":[0.9990844,0.000261176,0.0000578604,0.0002022602,0.0002265797,0.0001677726],"domain_scores_gemma":[0.9960399,0.002134348,0.0002831641,0.0005927209,0.0007621822,0.0001876329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009665142,0.0002947151,0.005583088,0.0001345977,0.00008502855,0.0002887475,0.0003534743,0.3507061,0.01876454,0.02869576,0.005265748,0.5888617],"study_design_scores_gemma":[0.000009372865,0.00005320294,0.0001954163,0.00001309642,0.000006087098,0.00003275429,0.00001217722,0.9891893,0.003745564,0.006168074,0.0005679812,0.000006993223],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03060404,0.0002992086,0.9656092,0.0002088588,0.00004933899,0.00003779086,0.00005976068,0.001810068,0.001321814],"genre_scores_gemma":[0.6471606,0.0002666165,0.345131,0.0005012736,0.0000915955,0.0001227942,0.0005625183,0.0004789102,0.005684668],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004127918,"threshold_uncertainty_score":0.01397252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1835225277663795,"score_gpt":0.360172484825532,"score_spread":0.1766499570591525,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}